Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A car, comprising: a lidar or long-range radar in a front of the car; a multi-focal camera in the front; one or more thermal imager(s) in the front or rear of the car; a processor coupled to the lidar, radar, multi-focal camera and thermal imagers, the processor running a plurality of trained neural networks for navigation, wherein processor controls the car; side cameras, side sonars or side radars coupled to the processor for blind spot detection, rear traffic alert, and parking; rear cameras, rear sonars or rear radars coupled to the processor for blind spot detection, rear traffic alert, and parking; and rolling wheels at a car bottom to facilitate lateral parking movement into a parking spot as guided by side sensors including sonar and camera sensors.
2. The car of claim 1 , wherein the processor determines lane boundaries and perform automatic parking.
Autonomous vehicle systems are designed to assist drivers in navigating and parking vehicles without manual intervention. A key challenge in such systems is accurately detecting lane boundaries and executing precise parking maneuvers to ensure safety and efficiency. This invention relates to an autonomous vehicle equipped with a processor that performs two primary functions. First, the processor analyzes sensor data to identify and track lane boundaries on the road. This involves processing inputs from cameras, LiDAR, or other sensors to detect lane markings, road edges, or other visual cues that define the lane structure. The system then uses this information to maintain the vehicle's position within the lane during driving. Second, the processor executes automatic parking by controlling the vehicle's steering, braking, and acceleration systems. The parking process involves selecting an appropriate parking space, calculating the necessary path to reach it, and maneuvering the vehicle into the space while avoiding obstacles. The system may also adjust the vehicle's position to ensure proper alignment and minimize the use of space. The combination of lane boundary detection and autonomous parking enhances the vehicle's ability to navigate complex environments and perform parking tasks without driver input, improving convenience and reducing the risk of accidents.
3. The car of claim 1 , wherein the multi-focal camera includes a lens receiving liquid to change a focal length of the lens.
A system for automotive imaging involves a multi-focal camera integrated into a vehicle to enhance situational awareness and safety. The camera dynamically adjusts its focal length to capture clear images at varying distances, addressing challenges in low-light or high-contrast environments. The camera includes a lens filled with a liquid that alters its refractive properties when subjected to external stimuli, such as electrical or thermal changes, enabling rapid focal length adjustments without mechanical components. This liquid-based lens system improves reliability and reduces wear compared to traditional autofocus mechanisms. The camera may also incorporate additional features like image stabilization and adaptive exposure control to further optimize image quality. The system is particularly useful for autonomous driving, advanced driver-assistance systems (ADAS), and real-time obstacle detection, providing drivers or automated systems with accurate visual data for decision-making. The liquid-filled lens design ensures precise and responsive focusing, enhancing overall vehicle safety and performance.
4. The car of claim 1 , wherein the multi-focal camera includes three lenses each with different focal length.
This invention relates to automotive imaging systems, specifically a car equipped with a multi-focal camera system designed to enhance situational awareness and object detection. The multi-focal camera includes three lenses, each with distinct focal lengths, allowing the system to capture images at varying depths of field simultaneously. This configuration enables the camera to provide a wide field of view while maintaining high-resolution details at different distances, improving the car's ability to detect and track objects in diverse driving environments. The multi-focal design reduces the need for multiple separate cameras, simplifying the system architecture and reducing cost. The lenses are arranged to minimize parallax errors, ensuring accurate depth perception and object localization. This setup is particularly useful for advanced driver-assistance systems (ADAS) and autonomous driving applications, where precise and comprehensive environmental sensing is critical. The system may also incorporate image processing algorithms to merge and analyze data from the different focal lengths, enhancing object recognition and tracking performance. By integrating multiple focal lengths into a single camera unit, the invention improves imaging efficiency and reliability in automotive applications.
5. The car of claim 1 , based on the emotion, drowsiness or fatigue, the processor adjusts autonomous driving to Traffic Signal Recognition, Lane Departure Warning, Collision Detection, or Pedestrian Detection.
Autonomous vehicle systems monitor driver state to enhance safety by adjusting driving assistance features. The system detects driver emotions, drowsiness, or fatigue using sensors and processes this data to determine the driver's condition. Based on the detected state, the vehicle's processor dynamically adjusts autonomous driving functions. If the driver is drowsy or fatigued, the system may prioritize safety features such as Traffic Signal Recognition to ensure compliance with traffic lights, Lane Departure Warning to prevent unintended lane drifting, Collision Detection to avoid accidents, or Pedestrian Detection to protect vulnerable road users. The adjustments are made in real-time to mitigate risks associated with impaired driver attention. This approach improves overall vehicle safety by proactively adapting assistance systems to the driver's cognitive and physical state. The system integrates sensor data, processing algorithms, and autonomous driving controls to create a responsive safety framework.
6. The car of claim 1 , comprising a remote processor to determine if a driver or a manufacturer of the car is at fault from an unreasonable control of the car.
This invention relates to automotive systems designed to assess fault in vehicle control incidents. The system includes a vehicle equipped with sensors and a remote processor that analyzes driving behavior to determine whether a driver or the vehicle manufacturer is at fault when the vehicle exhibits unreasonable control. The vehicle's sensors monitor various parameters, such as steering, braking, acceleration, and stability, to detect deviations from expected performance. The remote processor receives this data and applies predefined criteria to assess whether the vehicle's behavior was due to driver error or a manufacturing defect. If the processor identifies a fault in the vehicle's control systems, it may trigger alerts, diagnostics, or corrective actions. The system aims to improve safety by distinguishing between driver-related incidents and vehicle malfunctions, enabling targeted interventions and accountability. This technology is particularly useful for autonomous or semi-autonomous vehicles, where control decisions are shared between the driver and the vehicle's systems. The invention enhances accident investigation and liability determination by providing objective data analysis.
7. The car of claim 1 , wherein the processor recognizes an environment around the car.
Autonomous and semi-autonomous vehicles rely on environmental recognition to navigate safely and efficiently. Traditional systems often struggle with real-time processing of complex surroundings, leading to delays or inaccuracies in decision-making. This invention addresses these challenges by integrating advanced processing capabilities into a vehicle to enhance environmental awareness. The vehicle includes a processor configured to recognize and interpret the environment around the car. This involves analyzing data from sensors, cameras, and other input sources to detect obstacles, road conditions, traffic signals, and other relevant factors. The processor then processes this information to generate a comprehensive understanding of the surroundings, enabling the vehicle to make informed decisions for navigation, obstacle avoidance, and route optimization. The system may also incorporate machine learning algorithms to improve recognition accuracy over time by learning from new data and adapting to different driving conditions. By continuously monitoring and analyzing the environment, the vehicle can respond dynamically to changing conditions, such as sudden weather changes, unexpected obstacles, or traffic disruptions. This enhances safety and reliability, making the vehicle better equipped to handle real-world driving scenarios. The invention ensures that the vehicle operates with a high degree of autonomy while maintaining situational awareness, reducing the risk of accidents and improving overall driving efficiency.
8. The car of claim 1 , wherein the processor recognizes behaviors of people encountered.
This invention relates to an autonomous vehicle system designed to enhance situational awareness and safety by recognizing and interpreting human behaviors. The system includes a vehicle equipped with sensors, such as cameras and LiDAR, to detect and analyze the actions and intentions of pedestrians, cyclists, and other road users. A processor within the vehicle processes sensor data to identify patterns in human movement, such as walking speed, direction changes, or gestures, to predict potential interactions or hazards. The system may also classify behaviors into categories like cautious, distracted, or aggressive to adjust the vehicle's response accordingly. For example, if a pedestrian suddenly steps into the road, the vehicle may brake or alter its path to avoid collision. The processor may also use historical data or machine learning models to improve behavior recognition accuracy over time. The system aims to reduce accidents by anticipating human actions and ensuring safer navigation in dynamic environments.
9. The car of claim 1 , wherein the processor generates a response to people.
Autonomous vehicles face challenges in effectively communicating with pedestrians, cyclists, and other road users to ensure safety and clarity in navigation. Existing systems often lack intuitive or standardized methods for conveying intent, leading to confusion or misinterpretation. This invention addresses the problem by enhancing an autonomous vehicle with a processor that generates and outputs responses to people in the vehicle's environment. The processor analyzes sensor data, such as visual or audio inputs, to detect and interpret human actions, gestures, or signals. Based on this analysis, the processor generates appropriate responses, such as visual cues, auditory signals, or vehicle movements, to communicate the vehicle's intentions or acknowledge the presence of nearby individuals. For example, the vehicle may display a light pattern, emit a sound, or adjust its trajectory to indicate a turn or stop. The system ensures that interactions between the vehicle and people are clear, reducing the risk of accidents and improving overall road safety. The processor may also integrate with other vehicle systems, such as navigation or obstacle avoidance, to dynamically adjust responses based on real-time conditions. This approach provides a more human-centric and adaptive communication method for autonomous vehicles.
10. The car of claim 1 , wherein the processor communicates with nearby people through audio or visual responses.
This invention relates to an advanced car system designed to enhance communication between the vehicle and nearby individuals. The car includes a processor that enables interaction with people in the vicinity through audio or visual responses. The processor can generate spoken messages or display visual signals to convey information, such as warnings, instructions, or status updates. For example, the system may alert pedestrians of an approaching vehicle or provide directions to emergency responders. The processor may also receive input from sensors or user commands to tailor responses based on context, such as detecting a person's presence or recognizing specific gestures. The car's communication features improve safety and situational awareness by ensuring clear and timely exchanges between the vehicle and nearby individuals. The system may integrate with other vehicle functions, such as navigation or collision avoidance, to deliver relevant and actionable information. This technology is particularly useful in urban environments, crowded areas, or scenarios where direct human interaction with the vehicle is necessary.
11. A car, comprising: a lidar or long-range radar in a front of the car; a multi-focal camera in the front; one or more thermal imager(s) in the front or rear of the car; a processor coupled to the lidar, radar, multi-focal camera and thermal imagers, the processor running a plurality of trained neural networks for navigation or control the car; side cameras, side sonars or side radars coupled to the processor for blind spot detection, rear traffic alert, and parking; rear cameras, rear sonars or rear radars coupled to the processor for blind spot detection, rear traffic alert, and parking; and wherein the processor uses a trained neural network to make driving decisions for an autonomous car; and complies with one or more traffic rules on driving speed or lane changing, and ignoring the one or more traffic rules during an imminent accident, wherein a plurality of vehicle sensor parameters and traffic and weather conditions are featurized, and applying a law neural network trained on traffic case law or legal precedent.
This invention relates to an autonomous vehicle equipped with advanced sensing and decision-making systems to navigate and control the vehicle while adhering to traffic rules and legal precedents. The vehicle includes a front-mounted lidar or long-range radar for detecting obstacles and measuring distances, a multi-focal camera for capturing high-resolution images at varying depths, and one or more thermal imagers positioned at the front or rear to detect heat signatures, such as pedestrians or animals, in low-visibility conditions. The vehicle also features side and rear cameras, sonars, or radars to monitor blind spots, detect rear traffic, and assist with parking. A central processor integrates data from all sensors and runs multiple trained neural networks to process this information for navigation, control, and decision-making. The neural networks enable the vehicle to comply with traffic rules, such as speed limits and lane-changing protocols, while also prioritizing safety by overriding these rules during imminent accidents. The system featurizes vehicle sensor parameters, traffic conditions, and weather data, then applies a specialized "law neural network" trained on traffic case law and legal precedents to ensure decisions align with legal standards. This approach enhances autonomous driving safety and compliance with regulatory frameworks.
12. A car comprising: a lidar or long-range radar in a front of the car; a multi-focal camera in the front; one or more thermal imager(s) in the front or rear of the car; a processor coupled to the lidar, radar, multi-focal camera and thermal imagers, the processor running a plurality of trained neural networks for navigation or control the car; side cameras, side sonars or side radars coupled to the processor for blind spot detection, rear traffic alert, and parking; rear cameras, rear sonars or rear radars coupled to the processor for blind spot detection, rear traffic alert, and parking; and a low latency ultra-wide-band transceiver in communication with the processor, further comprising a remote processor coupled to a transceiver to offload processing from the processor.
This invention relates to an autonomous or semi-autonomous vehicle equipped with a comprehensive sensor suite and processing system for navigation, control, and safety. The vehicle includes a lidar or long-range radar mounted at the front to detect obstacles and map the environment. A multi-focal camera in the front captures high-resolution images at varying focal lengths, enhancing object recognition and depth perception. One or more thermal imagers are positioned at the front or rear to detect heat signatures, improving visibility in low-light or adverse weather conditions. A central processor runs multiple trained neural networks to analyze sensor data and make real-time decisions for navigation and vehicle control. Side-mounted cameras, sonars, or radars provide blind spot detection, rear traffic alerts, and assist with parking maneuvers. Similarly, rear-mounted cameras, sonars, or radars enhance situational awareness and safety. The vehicle also features a low-latency ultra-wideband transceiver for high-speed communication with a remote processor, enabling offloading of computationally intensive tasks to reduce onboard processing load. This distributed processing approach improves efficiency and responsiveness. The system integrates multiple sensors and advanced processing to enhance autonomous driving capabilities, safety, and environmental adaptability.
13. The car of claim 12 , wherein the processor determines lane boundaries and perform automatic steering when lane changing.
This invention relates to autonomous vehicle technology, specifically systems for lane boundary detection and automated lane-changing maneuvers. The system includes a processor that analyzes sensor data to identify lane markings on a roadway, determining the precise boundaries of adjacent lanes. Using this information, the processor calculates optimal steering adjustments to safely transition the vehicle from one lane to another without driver intervention. The system may integrate with other vehicle control modules to ensure smooth acceleration, braking, and steering during the lane change. The processor continuously monitors lane positions and vehicle dynamics to maintain proper alignment within the target lane after the maneuver. This technology addresses challenges in autonomous driving, such as accurately detecting lane boundaries in varying road conditions and executing precise, collision-free lane changes. The system enhances vehicle safety and convenience by automating a complex driving task that traditionally requires human judgment.
14. The car of claim 12 , wherein the processor determines lane boundaries and perform autonomous pedestrian and cyclist braking.
This invention relates to autonomous vehicle technology, specifically systems for detecting and responding to pedestrians and cyclists in real-time to prevent collisions. The system uses a processor to analyze sensor data, such as from cameras or LiDAR, to identify lane boundaries and track the positions of pedestrians and cyclists near the vehicle. The processor then calculates the risk of collision and autonomously applies the brakes if necessary to avoid an accident. The system may also adjust braking force based on the detected speed and trajectory of the pedestrians or cyclists. Additionally, the processor can distinguish between different types of road users, such as pedestrians and cyclists, to tailor braking responses appropriately. The invention improves safety by reducing human error in emergency braking scenarios and ensuring timely intervention when vulnerable road users are present. The system integrates with the vehicle's existing braking system to provide seamless and reliable collision avoidance.
15. The car of claim 12 , comprising a cabin camera facing a driver to determine attentiveness.
A system for monitoring driver attentiveness in a vehicle includes a cabin camera positioned to capture images or video of the driver. The camera is configured to analyze the driver's facial features, eye movements, head position, or other visual cues to assess attentiveness. The system may use image processing techniques, such as machine learning algorithms, to detect signs of distraction, drowsiness, or inattention. If the system determines that the driver is not attentive, it may trigger an alert, such as an audible or visual warning, or take corrective action, such as adjusting vehicle speed or steering. The system may also log data for later review or integrate with other vehicle safety features, such as collision avoidance systems. The camera may be mounted on the dashboard, steering column, or another suitable location within the vehicle cabin to ensure an unobstructed view of the driver. The system may operate continuously or at predetermined intervals to monitor the driver's state. The technology addresses the problem of driver distraction and fatigue, which are leading causes of vehicle accidents, by providing real-time feedback to improve safety.
16. The car of claim 12 , wherein a cabin camera performs one of driver authorization, gaze detection, eye tracking and texting detection, or occupant monitoring.
This invention relates to automotive systems that enhance safety and security through advanced cabin monitoring. The system includes a vehicle equipped with a cabin camera that performs multiple functions to monitor driver and occupant behavior. The camera is capable of driver authorization, verifying the identity of the driver before allowing vehicle operation. It also detects gaze direction and tracks eye movements to assess driver attention, helping prevent distracted driving. Additionally, the camera identifies texting or other phone-related distractions, alerting the driver or taking corrective actions. The system also monitors occupants, detecting their presence, posture, or other relevant conditions to enhance safety. The camera may be integrated with other vehicle systems to trigger warnings, restrict vehicle functions, or log incidents for later review. This technology addresses the need for improved driver monitoring to reduce accidents caused by inattention or unauthorized use, while also ensuring occupant safety through continuous observation. The system may operate in real-time, providing immediate feedback or interventions when unsafe behaviors are detected.
17. The car of claim 12 , comprising a wireless transceiver facing the driver to detect heart rate or respiratory rate.
A vehicle monitoring system includes a wireless transceiver positioned to face the driver, enabling non-invasive detection of physiological signals such as heart rate or respiratory rate. The transceiver operates using radio frequency signals, such as Doppler radar or ultra-wideband (UWB) technology, to measure subtle movements of the driver's chest or body caused by cardiac or respiratory activity. The system processes these signals to extract vital sign data, which can be used for driver health monitoring, fatigue detection, or safety applications. The transceiver may be integrated into the vehicle's dashboard, steering column, or other interior components, ensuring unobstructed signal transmission. The system may also include signal processing algorithms to filter noise and improve accuracy, as well as interfaces to display or transmit the collected data to external devices or cloud-based platforms. This technology addresses the need for passive, contactless health monitoring in vehicles to enhance driver safety and well-being without requiring wearable devices.
18. The car of claim 12 , wherein the processor receives images from a cabin camera for detecting emotion, drowsiness or fatigue from combination of determining facial expression, hand gesture, and heart rate or breathing rate.
This invention relates to an advanced automotive system designed to monitor driver and passenger well-being by analyzing physiological and behavioral cues. The system integrates a cabin camera to capture images of occupants, which are processed to detect emotional states, drowsiness, or fatigue. The analysis combines facial expression recognition, hand gesture tracking, and physiological measurements such as heart rate or breathing rate. By evaluating these inputs, the system can assess the occupant's condition in real-time, enabling interventions like alerts or adjustments to vehicle settings to enhance safety and comfort. The technology addresses the need for proactive monitoring in vehicles to prevent accidents caused by driver fatigue or emotional distress, leveraging multi-modal sensing for accurate and reliable detection. The system may also include additional features like adaptive climate control or entertainment adjustments based on the detected state, ensuring a responsive and personalized driving experience. The integration of these sensors and processing capabilities into a vehicle's onboard system provides a comprehensive solution for occupant well-being monitoring.
19. The car of claim 12 , comprising a cabin facing camera, wherein the processor detects a forgotten occupant in the car.
This invention relates to automotive safety systems designed to detect and prevent the accidental leaving of occupants, particularly children or pets, inside a vehicle. The system addresses the problem of unintentional occupant retention, which can lead to fatal consequences due to heatstroke or other hazards. The vehicle includes a cabin-facing camera that monitors the interior space. A processor analyzes the camera feed to identify and confirm the presence of an occupant who may have been forgotten. The system may also include additional sensors, such as weight sensors or motion detectors, to supplement the camera's detection capabilities. Upon detecting a forgotten occupant, the system triggers an alert, which may include visual or auditory warnings inside the vehicle, notifications to the driver's mobile device, or emergency alerts to authorities. The system may also lock the vehicle doors to prevent unauthorized access while ensuring the occupant's safety. The processor can differentiate between intentional and unintentional occupant retention, reducing false alarms. The invention aims to enhance vehicle safety by providing an automated and reliable method to detect and respond to forgotten occupants, mitigating risks associated with unattended individuals in vehicles.
Unknown
March 31, 2020
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